
HA historical average [1]}. HA models the data as a seasonal process and computes the predictions as a weighted average of the previous seasons.

ARIMA  integrated moving average model with Kalman filter which is widely used for time series forecasting.

VAR [2]} vector auto-regression.

SVR support vector regression.

FC-LSTM [3]} recurrent neural network with fully connected LSTM units.

WaveNet [4]} a dilated causal convolution network.

STGCN [5]} spatial-temporal GCN that combines 1D convolution with graph convolution.

GCRNN [1]} graph convolutional recurrent neural network.

DCRNN [1]} diffusion convolutional recurrent neural network.

